Tumor markers in breast cancer - European Group on Tumor Markers recommendations

Recommendations are presented for the routine clinical use of serum and tissue-based markers in the diagnosis and management of patients with breast cancer. Their low sensitivity and specificity preclude the use of serum markers such as the MUC-1 mucin glycoproteins ( CA 15.3, BR 27.29) and carcinoembryonic antigen in the diagnosis of early breast cancer. However, serial measurement of these markers can result in the early detection of recurrent disease as well as indicate the efficacy of therapy. Of the tissue-based markers, measurement of estrogen and progesterone receptors is mandatory in the selection of patients for treatment with hormone therapy, while HER-2 is essential in selecting patients with advanced breast cancer for treatment with Herceptin ( trastuzumab). Urokinase plasminogen activator and plasminogen activator inhibitor 1 are recently validated prognostic markers for lymph node-negative breast cancer patients and thus may be of value in selecting node-negative patients that do not require adjuvant chemotherapy. Copyright (C) 2005 S. Karger AG, Basel

Genome-wide association studies and genetic architecture of common human diseases

Genome-wide association scans provide the first successful method to identify genetic variation contributing to risk for common complex disease. Progress in identifying genes associated with melanoma show complex relationships between genes for pigmentation and the development of melanoma. Novel risk loci account for only a small fraction of the genetic variation contributing to this and many other diseases. Large meta-analyses find additional variants, but there is current debate about the contribution of common polymorphisms, rare polymorphisms or mutations to disease risk

The relevance of coagulation factor X protection of adenoviruses in human sera

Intravenous delivery of adenoviruses is the optimal route for many gene therapy applications. Once in the blood, coagulation factor X (FX) binds to the adenovirus capsid and protects the virion from natural antibody and classical complement-mediated neutralisation in mice. However, to date, no studies have examined the relevance of this FX/viral immune protective mechanism in human samples. In this study, we assessed the effects of blocking FX on adenovirus type 5 (Ad5) activity in the presence of human serum. FX prevented human IgM binding directly to the virus. In individual human sera samples (n=25), approximately half of those screened inhibited adenovirus transduction only when the Ad5–FX interaction was blocked, demonstrating that FX protected the virus from neutralising components in a large proportion of human sera. In contrast, the remainder of sera tested had no inhibitory effects on Ad5 transduction and FX armament was not required for effective gene transfer. In human sera in which FX had a protective role, Ad5 induced lower levels of complement activation in the presence of FX. We therefore demonstrate for the first time the importance of Ad–FX protection in human samples and highlight subject variability and species-specific differences as key considerations for adenoviral gene therapy

A stable pattern of EEG spectral coherence distinguishes children with autism from neuro-typical controls - a large case control study

<p>Abstract</p> <p>Background</p> <p>The autism rate has recently increased to 1 in 100 children. Genetic studies demonstrate poorly understood complexity. Environmental factors apparently also play a role. Magnetic resonance imaging (MRI) studies demonstrate increased brain sizes and altered connectivity. Electroencephalogram (EEG) coherence studies confirm connectivity changes. However, genetic-, MRI- and/or EEG-based diagnostic tests are not yet available. The varied study results likely reflect methodological and population differences, small samples and, for EEG, lack of attention to group-specific artifact.</p> <p>Methods</p> <p>Of the 1,304 subjects who participated in this study, with ages ranging from 1 to 18 years old and assessed with comparable EEG studies, 463 children were diagnosed with autism spectrum disorder (ASD); 571 children were neuro-typical controls (C). After artifact management, principal components analysis (PCA) identified EEG spectral coherence factors with corresponding loading patterns. The 2- to 12-year-old subsample consisted of 430 ASD- and 554 C-group subjects (n = 984). Discriminant function analysis (DFA) determined the spectral coherence factors' discrimination success for the two groups. Loading patterns on the DFA-selected coherence factors described ASD-specific coherence differences when compared to controls.</p> <p>Results</p> <p>Total sample PCA of coherence data identified 40 factors which explained 50.8% of the total population variance. For the 2- to 12-year-olds, the 40 factors showed highly significant group differences (<it>P </it>< 0.0001). Ten randomly generated split half replications demonstrated high-average classification success (C, 88.5%; ASD, 86.0%). Still higher success was obtained in the more restricted age sub-samples using the jackknifing technique: 2- to 4-year-olds (C, 90.6%; ASD, 98.1%); 4- to 6-year-olds (C, 90.9%; ASD 99.1%); and 6- to 12-year-olds (C, 98.7%; ASD, 93.9%). Coherence loadings demonstrated reduced short-distance and reduced, as well as increased, long-distance coherences for the ASD-groups, when compared to the controls. Average spectral loading per factor was wide (10.1 Hz).</p> <p>Conclusions</p> <p>Classification success suggests a stable coherence loading pattern that differentiates ASD- from C-group subjects. This might constitute an EEG coherence-based phenotype of childhood autism. The predominantly reduced short-distance coherences may indicate poor local network function. The increased long-distance coherences may represent compensatory processes or reduced neural pruning. The wide average spectral range of factor loadings may suggest over-damped neural networks.</p

Protein kinase Cδ expression in breast cancer as measured by real-time PCR, western blotting and ELISA

The protein kinase C (PKC) family of genes encode serine/threonine kinases that regulate proliferation, apoptosis, cell survival and migration. Multiple isoforms of PKC have been described, one of which is PKCδ. Currently, it is unclear whether PKCδ is involved in promoting or inhibiting cancer formation/progression. The aim of this study was therefore to investigate the expression of PKCδ in human breast cancer and relate its levels to multiple parameters of tumour progression. Protein kinase Cδ expression at the mRNA level was measured using real-time PCR (n=208) and at protein level by both immunoblotting (n=94) and ELISA (n=98). Following immunoblotting, two proteins were identified, migrating with molecular masses of 78 and 160 kDa. The 78 kDa protein is likely to be the mature form of PKCδ but the identity of the 160 kDa form is unknown. Levels of both these proteins correlated weakly but significantly with PKCδ concentrations determined by ELISA (for the 78 kDa form, r=0.444, P<0.005, n=91 and for the 160 kDa form, r=0.237, P=0.023, n=91) and with PKCδ mRNA levels (for the 78 kDa form, r=0.351, P=0.001, n=94 and for the 160 kDa form, r=0.216, P=0.037, n=94). Protein kinase Cδ mRNA expression was significantly higher in oestrogen receptor (ER)-positive compared with ER-negative tumours (P=0.007, Mann–Whitney U-test). Increasing concentrations of PKCδ mRNA were associated with reduced overall patient survival (P=0.004). Our results are consistent with a role for PKCδ in breast cancer progression

Location, location, location: considerations when using lightweight drones in challenging environments

Lightweight drones have emerged recently as a remote sensing survey tool of choice for ecologists, conservation practitioners and environmental scientists. In published work, there are plentiful details on the parameters and settings used for successful data capture, but in contrast there is a dearth of information describing the operational complexity of drone deployment. Information about the practices of flying in the field, whilst currently lacking, would be useful for others embarking on new drone-based investigations. As a group of drone-piloting scientists, we have operated lightweight drones for research in over 25 projects, in over 10 countries, and in polar, desert, coastal and tropical ecosystems, with many hundreds of hours of flying experience between us. The purpose of this paper was to document the lesser-reported methodological pitfalls of drone deployments so that other scientists can understand the spectrum of considerations that need to be accounted for prior to, and during drone survey flights. Herein, we describe the most common challenges encountered, alongside mitigation and remediation actions that increase the chances of safe and successful data capture. Challenges are grouped into the following categories: (i) pre-flight planning, (ii) flight operations, (iii) weather, (iv) redundancy, (v) data quality, (vi) batteries. We also discuss the importance of scientists undertaking ethical assessment of their drone practices, to identify and mitigate potential conflicts associated with drone use in particular areas. By sharing our experience, our intention is that the paper will assist those embarking on new drone deployments, increasing the efficacy of acquiring high-quality data from this new proximal aerial viewpoint.This work was supported by the Natural Environment Research Council [NE/K570009815], [NE/K500902/1] (to AMC), [NE/M016323/1] (to IHM-S), [NE/570009815] (to JPD) and the UK Technology Strategy Board [TS/K00266X/1] (to KA). JS and KA were partly supported by the European Space Agency contract No. 4000117644/16/NL/FF/gp

Variation in recognition of happy and sad facial expressions and self-reported depressive symptom severity: A prospective cohort study

Objective: Cognitive theories suggest people with depression interpret self-referential social information negatively. However, it is unclear whether these biases precede or follow depression. We investigated whether facial expression recognition was associated with depressive symptoms cross-sectionally and longitudinally. Methods: Prospective cohort study of people who had visited UK primary care in the past year reporting depressive symptoms (n = 509). Depressive symptoms were measured using the Patient Health Questionnaire (PHQ-9) at four time-points, 2 weeks apart. A computerised task assessed happy and sad facial expression recognition at three time-points (n = 505 at time 1). The unbiased hit rate measured ability to recognise emotions accounting for any general tendency to identify the emotion when it was not present. Results: The sample included the full range of depressive symptom severity, with 45% meeting diagnostic criteria for depression. There was no evidence that happy or sad unbiased hit rates were associated with concurrent or subsequent depressive symptoms. There was weak evidence that, for every additional face incorrectly classified as happy, concurrent PHQ-9 scores reduced by 0.05 of a point (95% CI = -0.10 to 0.002, p = 0.06 after adjustment for confounders). This association was strongest for more ambiguous facial expressions (interaction term p<0.001). Limitations: This was an observational study with relatively short follow-up (6 weeks) and small changes in depressive symptoms and emotion recognition. Only 7% of invited patients consented to participate. Conclusions: Reduced misclassifications of ambiguous faces as happy could be a state marker of depression, but was not associated with subsequent depressive symptoms. Future research should focus on the interpretation of ambiguous social informatio